基于近似分类质量的决策表属性约简算法

An Algorithm of Attributes Reduction in Decision Table Based on the Approximation Classified Quality

文章提出了一种基于近似分类质量的决策表属性约简算法,该原算法以空集作为初始属性约简,逐步增加使近似分类质量增加最大的属性,直至约简的近似分类质量等于所有条件属性的近似分类质量为止.文章同时分析了该算法的时间复杂度.并通过实例验证了该算法的有效性和合理性.

An algorithm of attribute reduction based on approximation classified quality is given. The algorithm takes empty set as the initial reduction, adding attribute with maximal change in approximation classified quality progressively, until approximation classified quality is equal with that of all attribute. The time complexity of the algorithm is analyzed and an example is investigated to verify this algorithm. The result show that the algorithm is effective and practical.